Meng Ye

Orcid: 0000-0003-2210-3396

Affiliations:
  • Rutgers University, Piscataway, NJ, USA


According to our database1, Meng Ye authored at least 17 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Continuous Spatio-Temporal Memory Networks for 4D Cardiac Cine MRI Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

Rate-My-LoRA: EFFICIENT AND ADAPTIVE FEDERATED MODEL TUNING FOR CARDIAC MRI SEGMENTATION.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation.
Proceedings of the Information Processing in Medical Imaging, 2025

Analysis of Cardiac Dynamic Global Function.
Proceedings of the Functional Imaging and Modeling of the Heart, 2025

2024
Learning Volumetric Neural Deformable Models to Recover 3D Regional Heart Wall Motion from Multi-Planar Tagged MRI.
CoRR, 2024

Unsupervised Exemplar-Based Image-to-Image Translation and Cascaded Vision Transformers for Tagged and Untagged Cardiac Cine MRI Registration.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Enhanced Deep Unrolled Models Applied to the CMRxRecon2024 Challenge.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Workshop, 2024

Rethinking Deep Unrolled Model for Accelerated MRI Reconstruction.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
SequenceMorph: A Unified Unsupervised Learning Framework for Motion Tracking on Cardiac Image Sequences.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers, 2023

Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
DeepRecon: Joint 2D Cardiac Segmentation and 3D Volume Reconstruction via a Structure-Specific Generative Method.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021
An Unsupervised 3D Recurrent Neural Network for Slice Misalignment Correction in Cardiac MR Imaging.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

Cardiac MR Image Sequence Segmentation with Temporal Motion Encoding.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020


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